A fuzzy-Bayesian model for supplier selection

Ferreira, Luciano Vaz; Borenstein, Denis

doi:10.1016/j.eswa.2012.01.068

Cited by 75 publications

(35 citation statements)

References 34 publications

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“…Extensive MCDM approaches have been proposed to deal with the supplier selection problem, such as the analytical hierarchy process [14,16], analytic network process [35,36], mathematical programming [37,38], data Envelopment Analysis [39,40], elimination and choice expressing reality (ELECTRE) [41,42], technique for order performance by similarity to ideal solution (TOPSIS) [43,44], fuzzy set theory [45], and their hybrids [15,16,19,43,46] and so on.…”

Section: Green Supplier Selection Approachesmentioning

confidence: 99%

Green Supplier Evaluation and Selection in Apparel Manufacturing Using a Fuzzy Multi-Criteria Decision-Making Approach

et al. 2017

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Abstract:With the increasing environmental awareness, apparel manufacturers have begun to consider environmental issues in supplier evaluation and selection. It is crucial to assess suppliers based on their environmental performance along with other criteria for supplier selection. This paper addresses the green supplier evaluation and selection problem in global apparel manufacturing by developing a methodological framework for green supplier evaluation and selection based on the triple bottom line principle and a fuzzy multi-criteria decision-making (MCDM) model. First, a green supplier evaluation criteria hierarchy based on the triple bottom line principle is established based on comprehensive literature review, on-site investigation and policy analysis. Then, a fuzzy MCDM model is presented to evaluate and select the best material supplier. Finally, a sensitivity analysis is conducted to verify the effectiveness of the proposed framework. Results show that the proposed framework can handle green supplier evaluation and selection in apparel manufacturing effectively.

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Section: Green Supplier Selection Approachesmentioning

confidence: 99%

Green Supplier Evaluation and Selection in Apparel Manufacturing Using a Fuzzy Multi-Criteria Decision-Making Approach

et al. 2017

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“…Chu and Varma (2012) presented a multiple-level multi-criteria decision-making method for evaluating suppliers. Ferreira and Borenstein (2012) proposed a fuzzy-Bayesian model for supplier selection. Atefeh Amindoust, Ahmed, Saghafinia, and Bahreininejad (2012) developed a ranking model based on a fuzzy inference system for sustainable supplier selection.…”

Section: Other Single Approachesmentioning

confidence: 99%

Supplier evaluation and selection in fuzzy environments: a review of MADM approaches

Ghorabaee

Amiri

Zavadskas

et al. 2017

Economic Research-Ekonomska Istraživanja

124

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In past years, the multi-attribute decision-making (MADM) approaches have been extensively applied by researchers to the supplier evaluation and selection problem. Many of these studies were performed in an uncertain environment described by fuzzy sets. This study provides a review of applications of MADM approaches for evaluation and selection of suppliers in a fuzzy environment. To this aim, a total of 339 publications were examined, including papers in peer-reviewed journals and reputable conferences and also some book chapters over the period of 2001 to 2016. These publications were extracted from many online databases and classified in some categories and subcategories according to the MADM approaches, and then they were analysed based on the frequency of approaches, number of citations, year of publication, country of origin and publishing journals. The results of this study show that the AHP and TOPSIS methods are the most popular approaches. Moreover, China and Taiwan are the top countries in terms of number of publications and number of citations, respectively. The top three journals with highest number of publications were:

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“…The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) [20,21] is a kind of MCDM method. Compared with other MCDM methods, such as fuzzy-set theory [22,23] and the Analytic Hierarchy Process (AHP) [24], TOPSIS has many merits such as the simplicity and insensitivity to the number of alternatives (or indicators) [25]. However, TOPSIS has difficulties in determining the weights of multiple alternatives and keeping the consistency of judgment [26].…”

Section: Introductionmentioning

confidence: 99%

A Smart MCDM Framework to Evaluate the Impact of Air Pollution on City Sustainability: A Case Study from China

2017

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Abstract:Air pollution has become one of the key environmental concerns in the urban sustainable development. It is important to evaluate the impact of air pollution on socioeconomic development since it is the prerequisite to enforce an effective prevention policy of air pollution. In this paper, we model the impact of air pollution on the urban economic development as a Multiple Criteria Decision Making (MCDM) problem. In particular, we propose a novel Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) analysis framework to evaluate multiple factors of air pollutants and economic development. Our method can overcome the drawbacks of conventional TOPSIS methods by using Bayesian regularization and the Back-Propagation (BP) neural network to optimize the weight training process. We have conducted a case study to evaluate our proposed framework.

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A fuzzy-Bayesian model for supplier selection

Cited by 75 publications

References 34 publications

Green Supplier Evaluation and Selection in Apparel Manufacturing Using a Fuzzy Multi-Criteria Decision-Making Approach

Green Supplier Evaluation and Selection in Apparel Manufacturing Using a Fuzzy Multi-Criteria Decision-Making Approach

Supplier evaluation and selection in fuzzy environments: a review of MADM approaches

A Smart MCDM Framework to Evaluate the Impact of Air Pollution on City Sustainability: A Case Study from China

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